ijerph-18-06325.pdf (8.66 MB)
Sensitivity analysis of emission models of parcel lockers vs. home delivery based on HBEFA
journal contribution
posted on 2021-06-21, 13:57 authored by Maren Schnieder, Christopher Hinde, Andrew WestAndrew WestGlobal concerns about the environmental effects (e.g., pollution, land use, noise) of last-mile deliveries are increasing. Parcel lockers are seen as an option to reduce these external effects of last-mile deliveries. The contributions of this paper are threefold: firstly, the research studies simulating the emissions caused by parcel delivery to lockers are summarized. Secondly, a demand model for parcel deliveries in New York City (NYC) is created for 365 days and delivery trips to lockers and homes are optimized for 20 “real-world” scenarios. Thirdly, using the emission factors included in the HandBook Emission Factors for Road Transport (HBEFA) database, the maximum percentage of customers who could pick up a parcel by car from parcel lockers that would result in fewer total emissions (driving customers + walking customers) than if home deliveries were adopted is calculated for various pollutants and scenario assumptions (i.e., street types, temperature, parking duration, level of service and vehicle drivetrain). This paper highlights how small changes in the calibration can significantly change the results and therefore using average values for emission factors or only considering one pollutant like most studies may not be appropriate.
Funding
EPSRC Centre for Doctoral Training in Embedded Intelligence
Engineering and Physical Sciences Research Council
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History
School
- Mechanical, Electrical and Manufacturing Engineering
- Science
Department
- Computer Science
Published in
International Journal of Environmental Research and Public HealthVolume
18Issue
12Publisher
MDPIVersion
- VoR (Version of Record)
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© The AuthorsPublisher statement
This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2021-06-08Publication date
2021-06-11Copyright date
2021ISSN
1661-7827eISSN
1660-4601Publisher version
Language
- en
Depositor
Maren Schnieder. Deposit date: 20 June 2021Article number
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